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http://enigma.ini.usc.edu/protocols/dti-protocols/

Pipeline which provides tools to extract whole-brain average and regional measurements from DTI images including FA, AD, RD and MD. Protocols for preprocessing, ENIGMA-DTI processing (skeletonization and ROI extraction), and GWAS analysis are available. Software tools used for each process are listed within the protocols.

Proper citation: ENIGMA-DTI Pipeline (RRID:SCR_014649) Copy   

•   Source: SciCrunch Registry

https://cismm.web.unc.edu/

Biomedical technology research center that develops force technologies applicable over a wide range of biological settings, from the single molecule to the tissue, with integrated systems that orchestrate facile instrument control, multimodal imaging, and analysis through visualization and modeling. The Force Microscope Technologies Core designs instruments in an area of science where there are unusual opportunities: the measurement of forces and the integration with optical microscopy. Force technologies play the obvious role of both measuring events in the sample and modifying the sample during the experiment. It is through the microscope that the force data is correlated with simultaneous 3D optical images. The force technology development includes the magnetic bead technology in the 3D Force Microscope project, Atomic Force Microscopy in the nanoManipulator project, and Control Software to drive the instrumentation. This core is focused on providing the physical capability to perform the experiments and probe structure/property correlations. The Ideal User Interfaces core makes the connection between the user and the instrument, the model building, and the data. This includes control systems that allow the user to move the bead inside the cell culture with a handheld pen and the visualization techniques to view the optical microscope data as a rendered 3D image collocated with the force data. Using data to create, change, and understand a model is the focus of the Advanced Model Fitting and Analysis core. The quantitative reduction of images to structural, shape, and velocity parameters is the goal of Image Analysis. The immediate understanding of correlations across image fields and between data sets in the challenge of Visualization. The power of combining the strength of a computer science graphics group with a microscopy technology group is most evident in the Graphics Hardware Acceleration project, which seeks to harness the speed of graphics processors for microscope data analysis and simulation. The Advanced Technology core pushes the boundaries of the Human Computer Interface through the investigation of improved techniques for the interaction of users with virtual environments, the real time lighting of virtual settings, and the enabling of multi-person collaboration. These techniques are validated and evaluated through physiological measures in virtual environments effectiveness evaluation studies.

Proper citation: Computer Integrated Systems for Microscopy and Manipulation (RRID:SCR_001413) Copy   

•   Source: SciCrunch Registry

http://octresearch.org/

Biomedical technology research center that pioneers and provides access to microscopic imaging instruments for biologic and clinical research. Optical coherence tomography (OCT) has evolved over the last two decades to become a standard of care for diagnostic ophthalmic imaging and is poised to make significant impact in the fields of cardiology and gastrointestinal endoscopy. Access to state-of-the-art instrumentation, however, has been limited to a relatively few research laboratories and the optimization of instruments for new biomedical applications has hindered the investigation of new opportunities. A major focus of CBORT will be to cultivate strategic research collaborations and respond to a pressing need for application-specific OCT instrumentation and hardware.

Proper citation: Center for Biomedical OCT Research (RRID:SCR_001418) Copy   

•   Source: SciCrunch Registry

http://www.biomemsrc.org/

Biomedical technology research center that provides biomedical investigators with novel microsystems engineering tools for biological discovery, diagnostic, prognostic, and therapeutic applications. Thrust areas of interest are the development of novel living cell-based, lab-on-a-chip type devices for sorting blood cells, for high-throughput biochemistry in small volumes, and for studying cellular behavior in controlled microenvironments.

Proper citation: BioMEMS Resource Center (RRID:SCR_001417) Copy   

•   Source: SciCrunch Registry

http://www.neuralgate.org/download/NeuralAct

Software to visualize electrocorticographic (ECoG) and possibly also other kinds of neural activity (EEG / EMG/ DOT) on a 3D model of the cortical surface. The tool has been used to produce cortical activation images and image sequences in several recent studies using ECoG. The tool is written in matlab. The package is thoroughly documented and includes a demo.

Proper citation: NeuralAct (RRID:SCR_002066) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/targetgene/

MATLAB tool to effectively identify potential therapeutic targets and drugs in cancer using genetic network-based approaches. It can rapidly extract genetic interactions from a precompiled database stored as a MATLAB MAT-file without the need to interrogate remote SQL databases. Millions of interactions involving thousands of candidate genes can be mapped to the genetic network within minutes. While TARGETgene is currently based on the gene network reported in (Wu et al.,Bioinformatics 26:807-813, 2010), it can be easily extended to allow the optional use of other developed gene networks. The simple graphical user interface also enables rapid, intuitive mapping and analysis of therapeutic targets at the systems level. By mapping predictions to drug-target information, TARGETgene may be used as an initial drug screening tool that identifies compounds for further evaluation. In addition, TARGETgene is expected to be applicable to identify potential therapeutic targets for any type or subtype of cancers, even those rare cancers that are not genetically recognized. Identification of Potential Therapeutic Targets * Prioritize potential therapeutic targets from thousands of candidate genes generated from high-throughput experiments using network-based metrics * Validate predictions (prioritization) using user-defined benchmark genes and curated cancer genes * Explore biologic information of selected targets through external databases (e.g., NCBI Entrez Gene) and gene function enrichment analysis Initial Drug Screening * Identify for further evaluation existing drugs and compounds that may act on the potential therapeutic targets identified by TARGETgene * Explore general information on identified drugs of interest through several external links Operating System: Windows XP / Vista / 7

Proper citation: TARGETgene (RRID:SCR_001392) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/sivic/

Software framework and application suite for processing and visualization of DICOM MR Spectroscopy data. Through the use of DICOM, SIVIC aims to facilitate the application of MRS in medical imaging studies.

Proper citation: Spectroscopic Imaging, VIsualization, and Computing (SIVIC) (RRID:SCR_027875) Copy   

•   Source: SciCrunch Registry

http://www.radiology.ucsf.edu/cind

Biomedical technology research center that develops and validates new imaging methods for detecting brain abnormalities in neurodegenerative diseases, including Alzheimer's disease, vascular dementia, frontotemporal dementia, Parkinson's disease, as well as epilepsy, depression, and other conditions associated with nerve loss in the brain. As people around the globe live longer, the impact of neurodegenerative diseases is expected to increase further with dire social and economical consequences for societies if no effective treatments are developed soon. The development at CIND is aimed to improve magnetic resonance imaging (MRI). The ultimate goal of the scientific program is to identify imaging markers that improve accuracy in diagnosing neurodegenerative diseases at early stages, achieve more reliable prognoses of disease progression, and facilitate the discovery of effective treatment interventions. In addition to addressing the general needs for studying neurodegenerative diseases, another focus of CIND concerns brain diseases associated with military service and war combat, such as post traumatic stress disorder (PTSD), brain trauma, gulf war illness and the long-term effects of these conditions on the mental health of veterans. The symbiosis between CIND and the Veterans Administration Medical Center in San Francisco makes this program uniquely suited to serve military veterans.

Proper citation: Center for Imaging of Neurodegenerative Diseases (RRID:SCR_001968) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/tumorsim/

Simulation software that generates pathological ground truth from a healthy ground truth. The software requires an input directory that describes a healthy anatomy (anatomical probabilities, mesh, diffusion tensor image, etc) and then outputs simulation images.

Proper citation: TumorSim (RRID:SCR_002604) Copy   

•   Source: SciCrunch Registry

http://www.fmri.wfubmc.edu/cms/software

Research group based in the Department of Radiology of Wake Forest University School of Medicine devoted to the application of novel image analysis methods to research studies. The ANSIR lab also maintains a fully-automated functional and structural image processing pipeline supporting the image storage and analysis needs of a variety of scientists and imaging studies at Wake Forest. Software packages and toolkits are currently available for download from the ANSIR Laboratory, including: WFU Biological Parametric Mapping Toolbox, WFU_PickAtlas, and Adaptive Staircase Procedure for E-Prime.

Proper citation: Advanced Neuroscience Imaging Research Laboratory Software Packages (RRID:SCR_002926) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/score/

A collection of methods for comparing the performance of different image algorithms. These methods generate quantitative scores that measure divergences to a standard.

Proper citation: SCORE (RRID:SCR_014165) Copy   

•   Source: SciCrunch Registry

https://neuron.yale.edu/neuron/

Software for computational neurophysiology. Simulation environment is used for building and using computational models of neurons and networks of neurons. NEURON Users Group can participate in collaborative development of documentation, tutorials, and software.

Proper citation: NEURON (RRID:SCR_017449) Copy   

•   Source: SciCrunch Registry

https://github.com/QTIM-Lab/DeepNeuro

Software Python package for neuroimaging data. Framework to design and train neural network architectures. Used in medical imaging community to ensure consistent performance of networks across variable users, institutions, and scanners.

Proper citation: DeepNeuro (RRID:SCR_016911) Copy   

•   Source: SciCrunch Registry

https://yeatmanlab.github.io/pyAFQ/

Software package focused on automated delineation of major fiber tracts in individual human brains, and quantification of tissue properties within the tracts.Software for automated processing and analysis of diffusion MRI data. Automates tractometry.

Proper citation: Automated Fiber Quantification in Python (RRID:SCR_023366) Copy   

•   Source: SciCrunch Registry

http://connectomes.utah.edu/

A web-compliant application that allows connectomics visualization by converting datasets to web-optimized tiles, delivering volume transforms to client devices, and providing groups of users with connectome annotation tools and data simultaneously via conventional internet connections. Viking is an extensible tool for connectomics analysis and is generalizable to histomics applications.

Proper citation: Viking Viewer for Connectomics (RRID:SCR_005986) Copy   

•   Source: SciCrunch Registry

http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/adapt/

Software tool as plug-in developed for ImageJ/FIJI platform to automatically detect and analyse cell migration and morphodynamics. Provides whole cell analysis of multiple cells, while also returning data on individual membrane protrusion events.

Proper citation: ADAPT (RRID:SCR_006769) Copy   

•   Source: SciCrunch Registry

http://www.physionet.org/

Collection of dissemination and exchange recorded biomedical signals and open-source software for analyzing them. Provides facilities for cooperative analysis of data and evaluation of proposed new algorithm. Providies free electronic access to PhysioBank data and PhysioToolkit software. Offers service and training via on-line tutorials to assist users at entry and more advanced levels. In cooperation with annual Computing in Cardiology conference, PhysioNet hosts series of challenges, in which researchers and students address unsolved problems of clinical or basic scientific interest using data and software provided by PhysioNet. All data included in PhysioBank, and all software included in PhysioToolkit, are carefully reviewed. Researchers are further invited to contribute data and software for review and possible inclusion in PhysioBank and PhysioToolkit. Please review guidelines before submitting material.

Proper citation: PhysioNet (RRID:SCR_007345) Copy   

•   Source: SciCrunch Registry

http://icatb.sourceforge.net/fusion/fusion_startup.php

A MATLAB toolbox which implements the joint Independent Component Analysis (ICA), parallel ICA and CCA with joint ICA methods. It is used to to extract the shared information across modalities like fMRI, EEG, sMRI and SNP data. * Environment: Win32 (MS Windows), Gnome, KDE * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1

Proper citation: Fusion ICA Toolbox (RRID:SCR_003494) Copy   

•   Source: SciCrunch Registry

http://synapses.clm.utexas.edu/tools/reconstruct/reconstruct.stm

A Windows (Win32) software application for montaging, aligning, tracing, measuring, and reconstructing objects from serial microscopic section images. The software is designed for microscopy in which section resolution is much less than section thickness, such as transmitted electron microscopy (EM) where the resolution is a few nanometers while the section thickness is many tens of nanometers. Reconstruct can easily handle series with hundreds of very large, high-resolution section images. It facilitates image cropping, scaling and alignment. Multiple images can be placed side-by-side to make a montage of a section from a mosaic of images. The alignment of adjacent sections can be rapidly compared by either blending the two sections or by flickering between them. Sections can be moved while blended. Reconstruct aids in the calibration of image size. Images taken at different magnifications can be combined, calibrated and aligned. Tools for tracing and editing of objects on sections are provided. Objects can be surfaced from the traces and previewed in an OpenGL-based 3D scene window. The 3D scene can be saved as a bitmap or as a VRML file.

Proper citation: Synapse Web Reconstruct (RRID:SCR_002716) Copy   

•   Source: SciCrunch Registry